## Machine Learning: MCQs Set – 23

#### Q221: The k-means algorithm is a

- (A) Supervised learning algorithm
- (B) Unsupervised learning algorithm
- (C) Semi-supervised learning algorithm
- (D) Weakly supervised learning algorithm

#### Q222: When the number of features increase

- (A) Computation time increases
- (B) Model becomes complex
- (C) Learning accuracy decreases
- (D) All of the above

#### Q223: For unsupervised learning we have ____ model.

- (A) interactive
- (B) predictive
- (C) descriptive
- (D) prescriptive

#### Q224: Engineering a good feature space is a crucial ___ for the success of any machine learning model.

- (A) Pre-requisite
- (B) Process
- (C) Objective
- (D) None of the above

#### Q225: In LDA, intra-class and inter-class ___ matrices are calculated.

- (A) Scatter
- (B) Adjacency
- (C) Similarity
- (D) None of the above

#### Q226: We can define this probability as p(A|B) = p(A,B)/p(B) if p(B) > 0

- (A) Conditional probability
- (B) Marginal probability
- (C) Bayes probability
- (D) Normal probability

#### Q227: Predicting whether a tumour is malignant or benign is an example of?

- (A) Unsupervised Learning
- (B) Supervised Regression Problem
- (C) Supervised Classification Problem
- (D) Categorical Attribute

- (A) Problem Identification
- (B) Identification of Required Data
- (C) Data Pre-processing
- (D) Definition of Training Data Set

#### Q229: Which of the following is true about SVM?

- (A) It is useful only in high-dimensional spaces
- (B) It requires less memory
- (C) SVM does not perform well when we have a large data set
- (D) SVM performs well when we have a large data set

#### Q230: When you find many noises in data, which of the following options would you consider in kNN?

- (A) Increase the value of k
- (B) Decrease the value of k
- (C) Noise does not depend on k
- (D) k = 0

## Answers:

**Question** | Q211 | Q222 | Q223 | Q224 | Q225 | Q226 | Q227 | Q228 | Q229 | Q230 |

**Answer** | B | D | C | A | A | A | C | C | D | A |

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